scholarly journals The Small Number System

2019 ◽  
Author(s):  
Eric Margolis
Keyword(s):  
Working Memory ◽  
Object Tracking ◽  
Mental Models ◽  
Number System ◽  
Human Mind ◽  
Specific Structure ◽  
Specific System ◽  
Domain Specific ◽  
System P ◽  
General Alternative

I argue that the human mind includes an innate domain-specific system for representing precise small numerical quantities. This theory contrasts with object-tracking theories and with domain-general theories that only make use of mental models. I argue that there is a good amount of evidence for innate representations of small numerical quantities and that such a domain-specific system has explanatory advantages when infants’ poor working memory is taken into account. I also show that the mental models approach requires previously unnoticed domain-specific structure and consequently that there is no domain-general alternative to an innate domain-specific small number system.

scholarly journals How do we measure attention? Using factor analysis to establish construct validity of neuropsychological tests

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Melissa Treviño ◽  
Xiaoshu Zhu ◽  
Yi Yi Lu ◽  
Luke S. Scheuer ◽  
Eliza Passell ◽  
...  
Keyword(s):  
Working Memory ◽  
Factor Analysis ◽  
Visual Search ◽  
Object Tracking ◽  
Visual Working Memory ◽  
Neuropsychological Tests ◽  
Digit Span ◽  
Digit Symbol ◽  
Attentional Capacity ◽  
Spatial Span

AbstractWe investigated whether standardized neuropsychological tests and experimental cognitive paradigms measure the same cognitive faculties. Specifically, do neuropsychological tests commonly used to assess attention measure the same construct as attention paradigms used in cognitive psychology and neuroscience? We built on the “general attention factor”, comprising several widely used experimental paradigms (Huang et al., 2012). Participants (n = 636) completed an on-line battery (TestMyBrain.org) of six experimental tests [Multiple Object Tracking, Flanker Interference, Visual Working Memory, Approximate Number Sense, Spatial Configuration Visual Search, and Gradual Onset Continuous Performance Task (Grad CPT)] and eight neuropsychological tests [Trail Making Test versions A & B (TMT-A, TMT-B), Digit Symbol Coding, Forward and Backward Digit Span, Letter Cancellation, Spatial Span, and Arithmetic]. Exploratory factor analysis in a subset of 357 participants identified a five-factor structure: (1) attentional capacity (Multiple Object Tracking, Visual Working Memory, Digit Symbol Coding, Spatial Span), (2) search (Visual Search, TMT-A, TMT-B, Letter Cancellation); (3) Digit Span; (4) Arithmetic; and (5) Sustained Attention (GradCPT). Confirmatory analysis in 279 held-out participants showed that this model fit better than competing models. A hierarchical model where a general cognitive factor was imposed above the five specific factors fit as well as the model without the general factor. We conclude that Digit Span and Arithmetic tests should not be classified as attention tests. Digit Symbol Coding and Spatial Span tap attentional capacity, while TMT-A, TMT-B, and Letter Cancellation tap search (or attention-shifting) ability. These five tests can be classified as attention tests.

scholarly journals Mental models accurately predict emotion transitions

2017 ◽  
Vol 114 (23) ◽  
pp. 5982-5987 ◽  
Author(s):  
Mark A. Thornton ◽  
Diana I. Tamir
Keyword(s):  
Social Interactions ◽  
Mental Models ◽  
Social Impact ◽  
Human Mind ◽  
High Accuracy ◽  
Accurate Information ◽  
Emotional States ◽  
State Representation ◽  
Emotion Dynamics ◽  
Accuracy Study

Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

scholarly journals Domain-general factors influencing numerical and arithmetic processing

2017 ◽  
Vol 3 (2) ◽  
pp. 112-132 ◽  
Author(s):  
André Knops ◽  
Hans-Christoph Nuerk ◽  
Silke M. Göbel
Keyword(s):  
Numerical Cognition ◽  
Model Building ◽  
Number System ◽  
Special Issue ◽  
Domain Specific ◽  
Versus Domain ◽  
Specific Factors ◽  
Arithmetic Performance ◽  
General Aspects ◽  
Future Theory

This special issue contains 18 articles that address the question how numerical processes interact with domain-general factors. We start the editorial with a discussion of how to define domain-general versus domain-specific factors and then discuss the contributions to this special issue grouped into two core numerical domains that are subject to domain-general influences (see Figure 1). The first group of contributions addresses the question how numbers interact with spatial factors. The second group of contributions is concerned with factors that determine and predict arithmetic understanding, performance and development. This special issue shows that domain-general (Table 1a) as well as domain-specific (Table 1b) abilities influence numerical and arithmetic performance virtually at all levels and make it clear that for the field of numerical cognition a sole focus on one or several domain-specific factors like the approximate number system or spatial-numerical associations is not sufficient. Vice versa, in most studies that included domain-general and domain-specific variables, domain-specific numerical variables predicted arithmetic performance above and beyond domain-general variables. Therefore, a sole focus on domain-general aspects such as, for example, working memory, to explain, predict and foster arithmetic learning is also not sufficient. Based on the articles in this special issue we conclude that both domain-general and domain-specific factors contribute to numerical cognition. But the how, why and when of their contribution still needs to be better understood. We hope that this special issue may be helpful to readers in constraining future theory and model building about the interplay of domain-specific and domain-general factors.

scholarly journals Decision Making Processes and Outcomes

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Julie Hicks Patrick ◽  
Jenessa C. Steele ◽  
S. Melinda Spencer
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Information Search ◽  
Linear Regression Analysis ◽  
Individual Characteristics ◽  
Decision Quality ◽  
Quality Data ◽  
Solution Quality ◽  
Strategic Processing ◽  
Domain Specific

The primary aim of this study was to examine the contributions of individual characteristics and strategic processing to the prediction of decision quality. Data were provided by 176 adults, ages 18 to 93 years, who completed computerized decision-making vignettes and a battery of demographic and cognitive measures. We examined the relations among age, domain-specific experience, working memory, and three measures of strategic information search to the prediction of solution quality using a 4-step hierarchical linear regression analysis. Working memory and two measures of strategic processing uniquely contributed to the variance explained. Results are discussed in terms of potential advances to both theory and intervention efforts.

Inverse number in dagaare

2021 ◽  
pp. 444-462
Author(s):  
Scott Grimm
Keyword(s):  
Number System ◽  
Formal Semantic ◽  
Semantic Classification ◽  
Lexical Semantic ◽  
Semantic Account ◽  
Number Systems ◽  
System P ◽  
Functional Grounding

This chapter examines the inverse number system in Dagaare (Gur; Niger–Congo). Inverse number systems possess a number morpheme which for some nouns encodes the plural interpretation while for others it encodes the singular interpretation. This chapter argues that a principled lexical semantic classification underlies the inverse number strategy in Dagaare, guiding whether for a particular noun the inverse morpheme codes the singular or the plural interpretation. The chapter further explores the functional grounding of inverse number, in terms of frequency and individuation, and presents a formal semantic account of the inverse number system.

Multicomponent Working Memory System with Distributed Executive Control

2020 ◽  
pp. 150-174 ◽  
Author(s):  
André Vandierendonck
Keyword(s):  
Working Memory ◽  
Executive Control ◽  
Memory System ◽  
General Information ◽  
Long Term Memory ◽  
Term Memory ◽  
Episodic Buffer ◽  
Domain Specific ◽  
Current Task

The working memory model with distributed executive control accounts for the interactions between working memory and multi-tasking performance. The working memory system supports planned actions by relying on two capacity-limited domain-general and two time-limited domain-specific modules. Domain-general modules are the episodic buffer and the executive module. The episodic buffer stores multimodal representations and uses attentional refreshment to counteract information loss and to consolidate information in episodic long-term memory. The executive module maintains domain-general information relevant for the current task. The phonological buffer and the visuospatial module are domain specific; the former uses inner speech to maintain and to rehearse phonological information, whereas the latter holds visual and spatial representations active by means of image revival. For its operation, working memory interacts with declarative and procedural long-term memory, gets input from sensory registers, and uses the motor system for output.

Human Cognitive Processes

2009 ◽  
pp. 1-33
Author(s):  
Slava Kalyuga
Keyword(s):  
Working Memory ◽  
Cognitive Architecture ◽  
Human Cognition ◽  
Long Term Memory ◽  
Domain Specific ◽  
Knowledge Based ◽  
Domain Specific Knowledge ◽  
And Performance ◽  
Memory Knowledge ◽  
High Level

One of the major components of our cognitive architecture, working memory, becomes overloaded if more than a few chunks of information are processed simultaneously. For example, we all experience this cognitive overload when trying to keep in memory an unfamiliar telephone number or add two four-digit numbers in the absence of a pen and paper. Similar in nature processing limitations of working memory represent a major factor influencing the effectiveness of human learning and performance, particularly in complex environments that require concurrent performance of multiple tasks. The learner prior domain-specific knowledge structures and associated levels of expertise are considered as means of reducing these limitations and guiding high-level knowledge-based cognitive activities. One of the most important results of studies in human cognition is that the available knowledge is a single most significant learner cognitive characteristic that influences learning and cognitive performance. Understanding the key role of long-term memory knowledge base in our cognition is important to the successful management of cognitive load in multimedia learning.

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